{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "f2a6d893",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "本接口即将停止更新，请尽快使用Pro版接口：https://tushare.pro/document/2\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\yzd\\anaconda3\\lib\\site-packages\\tushare\\stock\\trading.py:706: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  data = data.append(_get_k_data(url, dataflag,\n",
      "C:\\Users\\yzd\\anaconda3\\lib\\site-packages\\tushare\\stock\\trading.py:706: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  data = data.append(_get_k_data(url, dataflag,\n",
      "C:\\Users\\yzd\\anaconda3\\lib\\site-packages\\tushare\\stock\\trading.py:706: FutureWarning: The frame.append method is deprecated and will be removed from pandas in a future version. Use pandas.concat instead.\n",
      "  data = data.append(_get_k_data(url, dataflag,\n",
      "C:\\Users\\yzd\\anaconda3\\lib\\site-packages\\statsmodels\\tsa\\base\\tsa_model.py:471: ValueWarning: A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.\n",
      "  self._init_dates(dates, freq)\n",
      "C:\\Users\\yzd\\anaconda3\\lib\\site-packages\\statsmodels\\tsa\\base\\tsa_model.py:471: ValueWarning: A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.\n",
      "  self._init_dates(dates, freq)\n",
      "C:\\Users\\yzd\\anaconda3\\lib\\site-packages\\statsmodels\\tsa\\base\\tsa_model.py:471: ValueWarning: A date index has been provided, but it has no associated frequency information and so will be ignored when e.g. forecasting.\n",
      "  self._init_dates(dates, freq)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "            date    open   close    high     low     volume    code\n",
      "243   2019-01-02   6.439   6.412   6.620   6.369   152059.0  601012\n",
      "244   2019-01-03   6.424   6.455   6.600   6.298   180640.0  601012\n",
      "245   2019-01-04   6.463   6.636   6.659   6.231   254649.0  601012\n",
      "246   2019-01-07   6.659   6.828   6.871   6.655   199795.0  601012\n",
      "247   2019-01-08   6.852   6.856   6.879   6.750   196162.0  601012\n",
      "...          ...     ...     ...     ...     ...        ...     ...\n",
      "1320  2023-06-20  28.810  28.730  29.150  28.560   879686.0  601012\n",
      "1321  2023-06-21  28.650  27.990  29.060  27.970  1153692.0  601012\n",
      "1322  2023-06-26  27.690  28.010  28.550  27.360  1065610.0  601012\n",
      "1323  2023-06-27  28.050  28.180  28.750  27.650  1000901.0  601012\n",
      "1324  2023-06-28  28.130  29.320  29.420  27.910  2176752.0  601012\n",
      "\n",
      "[1082 rows x 7 columns]\n",
      "              open   close    high     low     volume    code\n",
      "date                                                         \n",
      "2019-01-02   6.439   6.412   6.620   6.369   152059.0  601012\n",
      "2019-01-03   6.424   6.455   6.600   6.298   180640.0  601012\n",
      "2019-01-04   6.463   6.636   6.659   6.231   254649.0  601012\n",
      "2019-01-07   6.659   6.828   6.871   6.655   199795.0  601012\n",
      "2019-01-08   6.852   6.856   6.879   6.750   196162.0  601012\n",
      "...            ...     ...     ...     ...        ...     ...\n",
      "2023-06-20  28.810  28.730  29.150  28.560   879686.0  601012\n",
      "2023-06-21  28.650  27.990  29.060  27.970  1153692.0  601012\n",
      "2023-06-26  27.690  28.010  28.550  27.360  1065610.0  601012\n",
      "2023-06-27  28.050  28.180  28.750  27.650  1000901.0  601012\n",
      "2023-06-28  28.130  29.320  29.420  27.910  2176752.0  601012\n",
      "\n",
      "[1082 rows x 6 columns]\n",
      "date\n",
      "2019-01-06     6.501000\n",
      "2019-01-13     7.203800\n",
      "2019-01-20     7.935400\n",
      "2019-01-27     8.301400\n",
      "2019-02-03     8.388200\n",
      "                ...    \n",
      "2023-06-04    28.888000\n",
      "2023-06-11    27.302000\n",
      "2023-06-18    27.940000\n",
      "2023-06-25    28.566667\n",
      "2023-07-02    28.503333\n",
      "Freq: W-SUN, Name: close, Length: 235, dtype: float64\n",
      "                               SARIMAX Results                                \n",
      "==============================================================================\n",
      "Dep. Variable:                  close   No. Observations:                  230\n",
      "Model:                 ARIMA(2, 0, 2)   Log Likelihood                -491.479\n",
      "Date:                Thu, 29 Jun 2023   AIC                            994.958\n",
      "Time:                        11:39:56   BIC                           1015.586\n",
      "Sample:                             0   HQIC                          1003.279\n",
      "                                - 230                                         \n",
      "Covariance Type:                  opg                                         \n",
      "==============================================================================\n",
      "                 coef    std err          z      P>|z|      [0.025      0.975]\n",
      "------------------------------------------------------------------------------\n",
      "const         28.4489     14.361      1.981      0.048       0.302      56.595\n",
      "ar.L1          1.5163      0.203      7.470      0.000       1.118       1.914\n",
      "ar.L2         -0.5224      0.201     -2.593      0.010      -0.917      -0.128\n",
      "ma.L1         -0.3793      0.202     -1.878      0.060      -0.775       0.016\n",
      "ma.L2          0.1085      0.067      1.609      0.108      -0.024       0.241\n",
      "sigma2         4.1196      0.293     14.077      0.000       3.546       4.693\n",
      "===================================================================================\n",
      "Ljung-Box (L1) (Q):                   0.00   Jarque-Bera (JB):                43.86\n",
      "Prob(Q):                              0.96   Prob(JB):                         0.00\n",
      "Heteroskedasticity (H):               9.04   Skew:                            -0.01\n",
      "Prob(H) (two-sided):                  0.00   Kurtosis:                         5.14\n",
      "===================================================================================\n",
      "\n",
      "Warnings:\n",
      "[1] Covariance matrix calculated using the outer product of gradients (complex-step).\n",
      "210    45.751010\n",
      "211    45.425043\n",
      "212    45.151681\n",
      "213    44.907460\n",
      "214    44.679943\n",
      "         ...    \n",
      "296    34.040904\n",
      "297    33.968779\n",
      "298    33.897585\n",
      "299    33.827309\n",
      "300    33.757939\n",
      "Name: predicted_mean, Length: 91, dtype: float64\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\yzd\\anaconda3\\lib\\site-packages\\statsmodels\\tsa\\base\\tsa_model.py:834: ValueWarning: No supported index is available. Prediction results will be given with an integer index beginning at `start`.\n",
      "  return get_prediction_index(\n"
     ]
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 1200x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 600x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import time\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import tushare as ts\n",
    "import statsmodels.api as sm\n",
    "\n",
    "if __name__ == '__main__':\n",
    "    data = ts.get_k_data('601012', start='20180101', end='20230628')\n",
    "    print(data)\n",
    "    data.to_csv('601012.csv', index=False)\n",
    "    data = pd.read_csv('601012.csv', index_col=0, parse_dates=[0])\n",
    "    print(data)\n",
    "    week = data['close'].resample('W').mean()\n",
    "    print(week)\n",
    "    stock = week['2018':'2023'].dropna()\n",
    "    stock.plot(figsize=(12, 8))\n",
    "    model = sm.tsa.arima.ARIMA(stock, order=(2, 0, 2))\n",
    "    result = model.fit()\n",
    "    x = result.summary()\n",
    "    print(x)\n",
    "    pred = result.predict(210, 300, dynamic=True)\n",
    "    print(pred)\n",
    "    plt.figure(figsize=(6, 6))\n",
    "    plt.plot(pred)\n",
    "    plt.plot(stock.values)\n",
    "    plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cfd91dd9",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.13"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
